VirPool: model-based estimation of SARS-CoV-2 variant proportions in wastewater samples

BMC Bioinformatics

Research

Boris Klempa¹  Kristína Boršová¹  Viktória Čabanová¹  Fabian Amman²  Andreas Bergthaler²  Broňa Brejová³  Askar Gafurov³  Andrej Baláž³  Tomáš Vinař³ 

[1] Biomedical Research Center, Slovak Academy of Sciences, Bratislava, Slovakia;CeMM Research Center for Molecular Medicine, Austrian Academy of Sciences, Lazarettgasse 14 AKH BT 25.3, 1090, Vienna, Austria;Institute of Hygiene and Applied Immunology, Center for Pathophysiology, Infectiology and Immunology, Medical University of Vienna, Kinderspitalsgasse 15, 1090, Vienna, Austria;Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava, Bratislava, Slovakia;

关键词: SARS-CoV-2;    Wastewater analysis;    Variant proportion estimation;    Probabilistic modeling;    Weighted mixture model;   

DOI  :  10.1186/s12859-022-05100-3

 received in 2022-06-21, accepted in 2022-12-06,  发布年份 2022

来源: Springer

【 摘 要 】

BackgroundThe genomes of SARS-CoV-2 are classified into variants, some of which are monitored as variants of concern (e.g. the Delta variant B.1.617.2 or Omicron variant B.1.1.529). Proportions of these variants circulating in a human population are typically estimated by large-scale sequencing of individual patient samples. Sequencing a mixture of SARS-CoV-2 RNA molecules from wastewater provides a cost-effective alternative, but requires methods for estimating variant proportions in a mixed sample.ResultsWe propose a new method based on a probabilistic model of sequencing reads, capturing sequence diversity present within individual variants, as well as sequencing errors. The algorithm is implemented in an open source Python program called VirPool. We evaluate the accuracy of VirPool on several simulated and real sequencing data sets from both Illumina and nanopore sequencing platforms, including wastewater samples from Austria and France monitoring the onset of the Alpha variant.ConclusionsVirPool is a versatile tool for wastewater and other mixed-sample analysis that can handle both short- and long-read sequencing data. Our approach does not require pre-selection of characteristic mutations for variant profiles, it is able to use the entire length of reads instead of just the most informative positions, and can also capture haplotype dependencies within a single read.

【 授权许可】

CC BY   
© The Author(s) 2022

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